class_docstr: A Fake executor for validating beam pipeline args passing.
class_docstr_tok: ["A","Fake","executor","for","validating","beam","pipeline","args","passing","."]
code: def Do(
      self,
      input_dict: Dict[str, List[types.Artifact]],
      output_dict: Dict[str, List[types.Artifact]],
      exec_properties: Dict[str, Any],
  ) -> None:
      assert "--runner=DirectRunner" in self._beam_pipeline_args
      model = output_dict["output_key"][0]
      model.name = "{0}.{1}.my_model".format(
          self._context.pipeline_info.id,
          self._context.pipeline_node.node_info.id,
      )
  
file_path: tfx/tfx/orchestration/portable/beam_executor_operator_test.py
imports: import os
  from typing import Any, Dict, List
  import tensorflow
  from tfx import types
  from tfx.dsl.components.base import base_beam_executor
  from tfx.orchestration.portable import beam_executor_operator
  from tfx.orchestration.portable import data_types
  from tfx.proto.orchestration import executable_spec_pb2
  from tfx.proto.orchestration import pipeline_pb2
  from tfx.types import standard_artifacts
  from tfx.utils import test_case_utils
  from google.protobuf import text_format
label_desc: Use image node_id 1 for calling the ValidateBeamPipelineArgsExecutor obj's underlying member method code with example usage: obj.Do(input_dict, output_dict, exec_properties) without return types